Self-cognition
Capability profiling, unknown detection, and correction loops with multi-source validation.
Resonix-AG documentation hub
Goal: provide a complete static-docs foundation you can deploy by uploading files only.
What Resonix-AG is
Resonix-AG is an autonomous AI agent stack focused on three pillars: self-cognition, autonomous learning, and permanent memory. It is based on the Resonix/OpenClaw ecosystem and designed for long-running agent workflows.
Unlike one-shot assistants, Resonix-AG can detect knowledge gaps, choose learning priorities, and preserve validated knowledge over time.
Core systems
Autonomous learning
Adaptive learning paths that move from fundamentals to validation-driven practice.
Permanent memory
Long retention layers for behavior traces, knowledge cards, and reusable learning strategies.
Gateway runtime
Deploy as a CLI + gateway with channel integrations and extension support.
Memory architecture summary
- Working memory: short TTL context for active tasks.
- Episodic memory: event history for reflective adaptation.
- Semantic memory: permanent validated knowledge cards.
- Program memory: durable strategy memory for future learning loops.
Recommended next steps
Start with the setup flow below, then move to installation and channel configuration.
1. Getting started
Environment checks, onboarding flow, and first-run validation.
2. Install options
Install script, source install, and troubleshooting pathways.
3. Channel setup
Choose channels and implement a clean rollout strategy.